Identify assets for cleanup in dbt with Secoda. Learn more about how you can automate workflows to turn hours into seconds. Do more with less and scale without the chaos.
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When it comes to maintaining the accuracy, reliability, and consistency of datasets, one crucial aspect is data cleanup. This process involves tagging data from dbt (database tool) that hasn't been accessed within a specified time period as 'for review'. By doing so, organizations can identify and address outdated or redundant data, improving overall data quality. This cleanup ensures that analyses and decisions relying on this data are valid and well-informed, ultimately enhancing the reliability of the information used for critical operations.
Using Secoda's automation capabilities with dbt, you can easily tag data that hasn't been accessed within a specific timeframe as 'for review' for cleanup. This process includes two parts: Triggers and Actions. Triggers allow you to set schedules like hourly or daily to initiate subsequent actions. Actions encompass various operations such as metadata updating and filtering. By combining these actions, you can create customized workflows that cater to the specific requirements of your team. With Secoda, you also have the ability to perform bulk updates to metadata in dbt, streamlining your data management tasks.
By integrating dbt with Secoda, data teams can enhance their data cleanup practices and effectively scale their operations. Secoda acts as a centralized hub for your company's data knowledge, combining important elements like data catalog, lineage, documentation, and monitoring into one comprehensive data management platform. This integration simplifies the process of managing and prioritizing assets, enabling data teams to streamline their workflows and make informed decisions.
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